Overview

Brought to you by YData

Dataset statistics

Number of variables15
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.3 MiB
Average record size in memory979.4 B

Variable types

Categorical5
Text7
Numeric3

Alerts

syscheck.size_after is highly overall correlated with syscheck.size_beforeHigh correlation
syscheck.size_before is highly overall correlated with syscheck.size_afterHigh correlation

Reproduction

Analysis started2025-06-01 06:10:09.096369
Analysis finished2025-06-01 06:10:14.095358
Duration5 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

syscheck.event
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size622.0 KiB
modified
3360 
deleted
3344 
added
3296 

Length

Max length8
Median length7
Mean length6.6768
Min length5

Characters and Unicode

Total characters66768
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowmodified
2nd rowdeleted
3rd rowdeleted
4th rowadded
5th rowmodified

Common Values

ValueCountFrequency (%)
modified 3360
33.6%
deleted 3344
33.4%
added 3296
33.0%

Length

2025-06-01T06:10:14.260139image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-06-01T06:10:14.361434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
modified 3360
33.6%
deleted 3344
33.4%
added 3296
33.0%

Most occurring characters

ValueCountFrequency (%)
d 23296
34.9%
e 16688
25.0%
i 6720
 
10.1%
m 3360
 
5.0%
o 3360
 
5.0%
f 3360
 
5.0%
l 3344
 
5.0%
t 3344
 
5.0%
a 3296
 
4.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 66768
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
d 23296
34.9%
e 16688
25.0%
i 6720
 
10.1%
m 3360
 
5.0%
o 3360
 
5.0%
f 3360
 
5.0%
l 3344
 
5.0%
t 3344
 
5.0%
a 3296
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 66768
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
d 23296
34.9%
e 16688
25.0%
i 6720
 
10.1%
m 3360
 
5.0%
o 3360
 
5.0%
f 3360
 
5.0%
l 3344
 
5.0%
t 3344
 
5.0%
a 3296
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 66768
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
d 23296
34.9%
e 16688
25.0%
i 6720
 
10.1%
m 3360
 
5.0%
o 3360
 
5.0%
f 3360
 
5.0%
l 3344
 
5.0%
t 3344
 
5.0%
a 3296
 
4.9%
Distinct9536
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size837.2 KiB
2025-06-01T06:10:14.658296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length45
Median length37
Mean length28.7177
Min length13

Characters and Unicode

Total characters287177
Distinct characters46
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9089 ?
Unique (%)90.9%

Sample

1st rowE:\Data\resource.pdf
2nd rowD:\Work\three.bat
3rd rowC:\Users\Project\Documents\success.jpg
4th rowD:\Work\career.dll
5th rowC:\Windows\Temp\field.bat
ValueCountFrequency (%)
c:\windows\system32\policy.pptx 3
 
< 0.1%
c:\users\public\videos\think.xlsx 3
 
< 0.1%
c:\programdata\choose.jpg 3
 
< 0.1%
c:\users\user2\desktop\nice.bat 3
 
< 0.1%
c:\users\project\documents\market.dll 3
 
< 0.1%
c:\users\public\videos\morning.xlsx 3
 
< 0.1%
c:\users\guest\documents\more.jpg 3
 
< 0.1%
c:\windows\temp\five.pptx 3
 
< 0.1%
c:\windows\system32\add.bat 3
 
< 0.1%
c:\users\public\videos\car.pptx 3
 
< 0.1%
Other values (9526) 9970
99.7%
2025-06-01T06:10:15.162614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
\ 31914
 
11.1%
s 25735
 
9.0%
e 24027
 
8.4%
t 15914
 
5.5%
o 15825
 
5.5%
r 15357
 
5.3%
a 11244
 
3.9%
: 10000
 
3.5%
. 10000
 
3.5%
i 8739
 
3.0%
Other values (36) 118422
41.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 287177
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
\ 31914
 
11.1%
s 25735
 
9.0%
e 24027
 
8.4%
t 15914
 
5.5%
o 15825
 
5.5%
r 15357
 
5.3%
a 11244
 
3.9%
: 10000
 
3.5%
. 10000
 
3.5%
i 8739
 
3.0%
Other values (36) 118422
41.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 287177
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
\ 31914
 
11.1%
s 25735
 
9.0%
e 24027
 
8.4%
t 15914
 
5.5%
o 15825
 
5.5%
r 15357
 
5.3%
a 11244
 
3.9%
: 10000
 
3.5%
. 10000
 
3.5%
i 8739
 
3.0%
Other values (36) 118422
41.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 287177
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
\ 31914
 
11.1%
s 25735
 
9.0%
e 24027
 
8.4%
t 15914
 
5.5%
o 15825
 
5.5%
r 15357
 
5.3%
a 11244
 
3.9%
: 10000
 
3.5%
. 10000
 
3.5%
i 8739
 
3.0%
Other values (36) 118422
41.2%
Distinct510
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size732.9 KiB
2025-06-01T06:10:15.487899image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length27
Median length22
Mean length18.0312
Min length9

Characters and Unicode

Total characters180312
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowread,write,hidden,system
2nd rowexec,archive,write
3rd rowarchive,read
4th rowhidden,archive
5th rowsystem,read,hidden
ValueCountFrequency (%)
exec,archive 131
 
1.3%
system,archive 131
 
1.3%
exec,system 128
 
1.3%
read,write 124
 
1.2%
read,hidden 122
 
1.2%
archive,system 121
 
1.2%
exec,hidden 119
 
1.2%
write,exec 119
 
1.2%
system,write 118
 
1.2%
hidden,archive 117
 
1.2%
Other values (500) 8770
87.7%
2025-06-01T06:10:15.955152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 35098
19.5%
, 20055
11.1%
r 15012
8.3%
i 14954
8.3%
d 14953
8.3%
s 10070
 
5.6%
c 10067
 
5.6%
a 10047
 
5.6%
t 10000
 
5.5%
h 9989
 
5.5%
Other values (6) 30067
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 180312
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 35098
19.5%
, 20055
11.1%
r 15012
8.3%
i 14954
8.3%
d 14953
8.3%
s 10070
 
5.6%
c 10067
 
5.6%
a 10047
 
5.6%
t 10000
 
5.5%
h 9989
 
5.5%
Other values (6) 30067
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 180312
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 35098
19.5%
, 20055
11.1%
r 15012
8.3%
i 14954
8.3%
d 14953
8.3%
s 10070
 
5.6%
c 10067
 
5.6%
a 10047
 
5.6%
t 10000
 
5.5%
h 9989
 
5.5%
Other values (6) 30067
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 180312
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 35098
19.5%
, 20055
11.1%
r 15012
8.3%
i 14954
8.3%
d 14953
8.3%
s 10070
 
5.6%
c 10067
 
5.6%
a 10047
 
5.6%
t 10000
 
5.5%
h 9989
 
5.5%
Other values (6) 30067
16.7%
Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size628.7 KiB
mode
1057 
mtime
1041 
group
1028 
size
994 
owner
937 
Other values (20)
4943 

Length

Max length11
Median length10
Mean length7.3675
Min length4

Characters and Unicode

Total characters73675
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowowner,mode
2nd rowmode,size
3rd rowgroup
4th rowmtime
5th rowmode

Common Values

ValueCountFrequency (%)
mode 1057
 
10.6%
mtime 1041
 
10.4%
group 1028
 
10.3%
size 994
 
9.9%
owner 937
 
9.4%
mode,owner 281
 
2.8%
owner,mode 267
 
2.7%
group,size 264
 
2.6%
mtime,size 261
 
2.6%
group,mode 261
 
2.6%
Other values (15) 3609
36.1%

Length

2025-06-01T06:10:16.112557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
mode 1057
 
10.6%
mtime 1041
 
10.4%
group 1028
 
10.3%
size 994
 
9.9%
owner 937
 
9.4%
mode,owner 281
 
2.8%
owner,mode 267
 
2.7%
group,size 264
 
2.6%
mtime,size 261
 
2.6%
group,mode 261
 
2.6%
Other values (15) 3609
36.1%

Most occurring characters

ValueCountFrequency (%)
e 11924
16.2%
m 9079
12.3%
o 8985
12.2%
i 5958
8.1%
r 5942
8.1%
, 4943
 
6.7%
d 3043
 
4.1%
p 3019
 
4.1%
g 3019
 
4.1%
u 3019
 
4.1%
Other values (5) 14744
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 73675
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 11924
16.2%
m 9079
12.3%
o 8985
12.2%
i 5958
8.1%
r 5942
8.1%
, 4943
 
6.7%
d 3043
 
4.1%
p 3019
 
4.1%
g 3019
 
4.1%
u 3019
 
4.1%
Other values (5) 14744
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 73675
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 11924
16.2%
m 9079
12.3%
o 8985
12.2%
i 5958
8.1%
r 5942
8.1%
, 4943
 
6.7%
d 3043
 
4.1%
p 3019
 
4.1%
g 3019
 
4.1%
u 3019
 
4.1%
Other values (5) 14744
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 73675
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 11924
16.2%
m 9079
12.3%
o 8985
12.2%
i 5958
8.1%
r 5942
8.1%
, 4943
 
6.7%
d 3043
 
4.1%
p 3019
 
4.1%
g 3019
 
4.1%
u 3019
 
4.1%
Other values (5) 14744
20.0%

syscheck.size_before
Real number (ℝ)

High correlation 

Distinct9971
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean994645.31
Minimum114
Maximum1999357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-01T06:10:16.285462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum114
5-th percentile96616.35
Q1495411.5
median990035
Q31495918.5
95-th percentile1893454.2
Maximum1999357
Range1999243
Interquartile range (IQR)1000507

Descriptive statistics

Standard deviation577682.05
Coefficient of variation (CV)0.58079201
Kurtosis-1.2046663
Mean994645.31
Median Absolute Deviation (MAD)499493
Skewness0.0071674874
Sum9.9464531 × 109
Variance3.3371655 × 1011
MonotonicityNot monotonic
2025-06-01T06:10:16.524598image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1560817 2
 
< 0.1%
641137 2
 
< 0.1%
1889340 2
 
< 0.1%
1887353 2
 
< 0.1%
1216565 2
 
< 0.1%
1376923 2
 
< 0.1%
40517 2
 
< 0.1%
301311 2
 
< 0.1%
1776853 2
 
< 0.1%
1710603 2
 
< 0.1%
Other values (9961) 9980
99.8%
ValueCountFrequency (%)
114 1
< 0.1%
439 1
< 0.1%
492 1
< 0.1%
498 1
< 0.1%
552 1
< 0.1%
976 1
< 0.1%
1012 1
< 0.1%
1506 1
< 0.1%
1730 1
< 0.1%
2142 1
< 0.1%
ValueCountFrequency (%)
1999357 1
< 0.1%
1998265 1
< 0.1%
1998126 1
< 0.1%
1997906 1
< 0.1%
1997711 1
< 0.1%
1997541 1
< 0.1%
1997534 1
< 0.1%
1997330 1
< 0.1%
1997181 1
< 0.1%
1996819 1
< 0.1%

syscheck.size_after
Real number (ℝ)

High correlation 

Distinct9358
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1005282.4
Minimum1
Maximum2486304
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-01T06:10:16.849311image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q1489323
median1002104.5
Q31500248.8
95-th percentile2038771.4
Maximum2486304
Range2486303
Interquartile range (IQR)1010925.8

Descriptive statistics

Standard deviation626674.75
Coefficient of variation (CV)0.62338182
Kurtosis-0.97210074
Mean1005282.4
Median Absolute Deviation (MAD)504644
Skewness0.10856673
Sum1.0052824 × 1010
Variance3.9272125 × 1011
MonotonicityNot monotonic
2025-06-01T06:10:17.150642image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 627
 
6.3%
1627014 2
 
< 0.1%
496540 2
 
< 0.1%
599310 2
 
< 0.1%
289095 2
 
< 0.1%
956870 2
 
< 0.1%
917770 2
 
< 0.1%
229628 2
 
< 0.1%
2014090 2
 
< 0.1%
914011 2
 
< 0.1%
Other values (9348) 9355
93.5%
ValueCountFrequency (%)
1 627
6.3%
241 1
 
< 0.1%
333 1
 
< 0.1%
864 1
 
< 0.1%
1057 1
 
< 0.1%
2167 1
 
< 0.1%
2427 1
 
< 0.1%
3739 1
 
< 0.1%
4159 1
 
< 0.1%
4527 1
 
< 0.1%
ValueCountFrequency (%)
2486304 1
< 0.1%
2456610 1
< 0.1%
2455974 1
< 0.1%
2453237 1
< 0.1%
2449228 1
< 0.1%
2446368 1
< 0.1%
2438214 1
< 0.1%
2436302 1
< 0.1%
2429813 1
< 0.1%
2427748 1
< 0.1%
Distinct9983
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size781.4 KiB
2025-06-01T06:10:17.835795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters230000
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9966 ?
Unique (%)99.7%

Sample

1st rowMay 20, 2025 @ 21:37:28
2nd rowMay 16, 2025 @ 20:41:05
3rd rowMay 11, 2025 @ 19:48:23
4th rowMay 24, 2025 @ 06:14:30
5th rowMay 26, 2025 @ 13:20:09
ValueCountFrequency (%)
may 10000
20.0%
2025 10000
20.0%
10000
20.0%
07 394
 
0.8%
05 386
 
0.8%
17 378
 
0.8%
14 365
 
0.7%
18 365
 
0.7%
22 362
 
0.7%
20 362
 
0.7%
Other values (9444) 17388
34.8%
2025-06-01T06:10:18.692930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40000
17.4%
2 32548
14.2%
0 24524
10.7%
: 20000
8.7%
5 17288
7.5%
1 14897
 
6.5%
M 10000
 
4.3%
a 10000
 
4.3%
y 10000
 
4.3%
@ 10000
 
4.3%
Other values (7) 40743
17.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 230000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
40000
17.4%
2 32548
14.2%
0 24524
10.7%
: 20000
8.7%
5 17288
7.5%
1 14897
 
6.5%
M 10000
 
4.3%
a 10000
 
4.3%
y 10000
 
4.3%
@ 10000
 
4.3%
Other values (7) 40743
17.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 230000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
40000
17.4%
2 32548
14.2%
0 24524
10.7%
: 20000
8.7%
5 17288
7.5%
1 14897
 
6.5%
M 10000
 
4.3%
a 10000
 
4.3%
y 10000
 
4.3%
@ 10000
 
4.3%
Other values (7) 40743
17.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 230000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
40000
17.4%
2 32548
14.2%
0 24524
10.7%
: 20000
8.7%
5 17288
7.5%
1 14897
 
6.5%
M 10000
 
4.3%
a 10000
 
4.3%
y 10000
 
4.3%
@ 10000
 
4.3%
Other values (7) 40743
17.7%
Distinct9979
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size781.4 KiB
2025-06-01T06:10:19.357922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters230000
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9958 ?
Unique (%)99.6%

Sample

1st rowMay 20, 2025 @ 22:01:23
2nd rowMay 16, 2025 @ 20:43:15
3rd rowMay 11, 2025 @ 20:24:27
4th rowMay 24, 2025 @ 06:40:59
5th rowMay 26, 2025 @ 14:14:22
ValueCountFrequency (%)
may 10000
20.0%
2025 10000
20.0%
10000
20.0%
07 391
 
0.8%
17 381
 
0.8%
05 380
 
0.8%
22 366
 
0.7%
20 365
 
0.7%
18 365
 
0.7%
14 363
 
0.7%
Other values (9452) 17389
34.8%
2025-06-01T06:10:20.202691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40000
17.4%
2 32484
14.1%
0 24736
10.8%
: 20000
8.7%
5 17103
7.4%
1 14879
 
6.5%
M 10000
 
4.3%
a 10000
 
4.3%
y 10000
 
4.3%
@ 10000
 
4.3%
Other values (7) 40798
17.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 230000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
40000
17.4%
2 32484
14.1%
0 24736
10.8%
: 20000
8.7%
5 17103
7.4%
1 14879
 
6.5%
M 10000
 
4.3%
a 10000
 
4.3%
y 10000
 
4.3%
@ 10000
 
4.3%
Other values (7) 40798
17.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 230000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
40000
17.4%
2 32484
14.1%
0 24736
10.8%
: 20000
8.7%
5 17103
7.4%
1 14879
 
6.5%
M 10000
 
4.3%
a 10000
 
4.3%
y 10000
 
4.3%
@ 10000
 
4.3%
Other values (7) 40798
17.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 230000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
40000
17.4%
2 32484
14.1%
0 24736
10.8%
: 20000
8.7%
5 17103
7.4%
1 14879
 
6.5%
M 10000
 
4.3%
a 10000
 
4.3%
y 10000
 
4.3%
@ 10000
 
4.3%
Other values (7) 40798
17.7%
Distinct9383
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2025-06-01T06:10:20.559374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length64
Median length64
Mean length58.4832
Min length32

Characters and Unicode

Total characters584832
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8931 ?
Unique (%)89.3%

Sample

1st row5561e1c0a579fab5c129c76ef2995e4062566fb197ee2c934aced8f5491db1ab
2nd row3c7631e0f7496bea8ee63d79d28969a4d81982030bd0914a919040c0b0f32fc1
3rd row445d870daa4fd41447c47a82550b17441706755f7699bfd8e70dba2f8007002e
4th row035cfdbd8ccc19822ffe29ef0d53d8100e262ea08bddf45e524c2d5cc7184f60
5th row7c42e63ce655761f78d841e46c541cbb10cd79a8b2c8e4fa05537427ad316eee
ValueCountFrequency (%)
49b4fb56524ed18969b6f58a96cc51f2 6
 
0.1%
627f59dd484237f42eae68c679afe678 6
 
0.1%
ef938dd97096f0cd6223901aacb94c85 5
 
< 0.1%
196019e10283118d62083e28d82f1ca7 5
 
< 0.1%
fc0560a3fea454812155dbe5d60fe072 4
 
< 0.1%
05c66c94f4d8c84d302f81d0f912fc85 4
 
< 0.1%
8a1465a423cad5250285437b6f58472e 4
 
< 0.1%
47269be6bb27403624f1e22e0033349c 4
 
< 0.1%
8f9d4b6d2be40491e2005ed195255fa7 4
 
< 0.1%
f9bbe2bb91b15fa0e4be4ae7f87d1e36 4
 
< 0.1%
Other values (9373) 9954
99.5%
2025-06-01T06:10:21.047054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 36906
 
6.3%
2 36798
 
6.3%
5 36795
 
6.3%
c 36768
 
6.3%
b 36760
 
6.3%
0 36752
 
6.3%
3 36723
 
6.3%
a 36692
 
6.3%
7 36516
 
6.2%
8 36377
 
6.2%
Other values (6) 217745
37.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 584832
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4 36906
 
6.3%
2 36798
 
6.3%
5 36795
 
6.3%
c 36768
 
6.3%
b 36760
 
6.3%
0 36752
 
6.3%
3 36723
 
6.3%
a 36692
 
6.3%
7 36516
 
6.2%
8 36377
 
6.2%
Other values (6) 217745
37.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 584832
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4 36906
 
6.3%
2 36798
 
6.3%
5 36795
 
6.3%
c 36768
 
6.3%
b 36760
 
6.3%
0 36752
 
6.3%
3 36723
 
6.3%
a 36692
 
6.3%
7 36516
 
6.2%
8 36377
 
6.2%
Other values (6) 217745
37.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 584832
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4 36906
 
6.3%
2 36798
 
6.3%
5 36795
 
6.3%
c 36768
 
6.3%
b 36760
 
6.3%
0 36752
 
6.3%
3 36723
 
6.3%
a 36692
 
6.3%
7 36516
 
6.2%
8 36377
 
6.2%
Other values (6) 217745
37.2%
Distinct9320
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2025-06-01T06:10:21.420856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length64
Median length64
Mean length58.0992
Min length32

Characters and Unicode

Total characters580992
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8846 ?
Unique (%)88.5%

Sample

1st rowa068c40f0c8cdabad580b70297ad0e3d070d49403ebc0b48218b6ca6c750fe19
2nd row96e1a43126806263aa4f49243f404651731446a290778adcac5ce9e3ed0c7dda
3rd row9cdd8b840a7d5609047e6a45f2f2e96b1cb4a6750ec5c82c9ba6b5c000a18113
4th row236e336691c3df827e1cef726a7a44dee65a3e86abb6855c537ef4fa186a1255
5th row58c48678ab5e2bfec68d3e4ef15beda80b49877796539677af9d166f99483f64
ValueCountFrequency (%)
bbdd815e4a7d9f30c5a36c797024007e 7
 
0.1%
e244a01a9b689f4c7f4abd12679bbb1e 6
 
0.1%
788f52b065809454d6833743c0e5d54a 5
 
< 0.1%
1f343516a0f4c5865255a486f638512c 5
 
< 0.1%
4d425ef3e3ae3afc66c4b9205fb23054 5
 
< 0.1%
22a58adb7e2d839268ff49077745f3f4 5
 
< 0.1%
f765d6641943bdb7277318d53274a92c 5
 
< 0.1%
3a47275f87422abccebf3e698624da7d 5
 
< 0.1%
d5679ccbbf6ab8ea71c10f5f9dfdd60a 4
 
< 0.1%
7f9eff4b71002024f87e6ffd356482c9 4
 
< 0.1%
Other values (9310) 9949
99.5%
2025-06-01T06:10:21.926041image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 36617
 
6.3%
3 36606
 
6.3%
b 36566
 
6.3%
5 36458
 
6.3%
2 36418
 
6.3%
9 36415
 
6.3%
e 36394
 
6.3%
a 36300
 
6.2%
f 36255
 
6.2%
d 36235
 
6.2%
Other values (6) 216728
37.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 580992
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 36617
 
6.3%
3 36606
 
6.3%
b 36566
 
6.3%
5 36458
 
6.3%
2 36418
 
6.3%
9 36415
 
6.3%
e 36394
 
6.3%
a 36300
 
6.2%
f 36255
 
6.2%
d 36235
 
6.2%
Other values (6) 216728
37.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 580992
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 36617
 
6.3%
3 36606
 
6.3%
b 36566
 
6.3%
5 36458
 
6.3%
2 36418
 
6.3%
9 36415
 
6.3%
e 36394
 
6.3%
a 36300
 
6.2%
f 36255
 
6.2%
d 36235
 
6.2%
Other values (6) 216728
37.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 580992
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 36617
 
6.3%
3 36606
 
6.3%
b 36566
 
6.3%
5 36458
 
6.3%
2 36418
 
6.3%
9 36415
 
6.3%
e 36394
 
6.3%
a 36300
 
6.2%
f 36255
 
6.2%
d 36235
 
6.2%
Other values (6) 216728
37.3%

syscheck.uid_after
Real number (ℝ)

Distinct6022
Distinct (%)60.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5493.9852
Minimum1000
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-01T06:10:22.097874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1475.95
Q13241.75
median5490
Q37739.25
95-th percentile9539
Maximum9999
Range8999
Interquartile range (IQR)4497.5

Descriptive statistics

Standard deviation2594.2622
Coefficient of variation (CV)0.47220044
Kurtosis-1.2135147
Mean5493.9852
Median Absolute Deviation (MAD)2249
Skewness0.017650819
Sum54939852
Variance6730196.5
MonotonicityNot monotonic
2025-06-01T06:10:22.567584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9983 6
 
0.1%
8823 6
 
0.1%
3849 6
 
0.1%
4171 6
 
0.1%
2260 6
 
0.1%
2524 6
 
0.1%
2484 6
 
0.1%
2749 6
 
0.1%
1611 6
 
0.1%
6790 5
 
0.1%
Other values (6012) 9941
99.4%
ValueCountFrequency (%)
1000 1
 
< 0.1%
1002 1
 
< 0.1%
1003 3
< 0.1%
1004 1
 
< 0.1%
1005 1
 
< 0.1%
1007 1
 
< 0.1%
1008 1
 
< 0.1%
1009 1
 
< 0.1%
1012 1
 
< 0.1%
1013 1
 
< 0.1%
ValueCountFrequency (%)
9999 1
 
< 0.1%
9998 1
 
< 0.1%
9997 1
 
< 0.1%
9994 3
< 0.1%
9993 3
< 0.1%
9992 1
 
< 0.1%
9991 2
 
< 0.1%
9990 2
 
< 0.1%
9987 3
< 0.1%
9983 6
0.1%
Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size608.4 KiB
User5
1033 
User1
1025 
Admin
1023 
User3
1006 
System
1005 
Other values (5)
4908 

Length

Max length7
Median length5
Mean length5.2919
Min length5

Characters and Unicode

Total characters52919
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUser4
2nd rowUser2
3rd rowSystem
4th rowUser4
5th rowUser1

Common Values

ValueCountFrequency (%)
User5 1033
10.3%
User1 1025
10.2%
Admin 1023
10.2%
User3 1006
10.1%
System 1005
10.1%
User6 1000
10.0%
User4 994
9.9%
Guest 990
9.9%
User2 967
9.7%
Project 957
9.6%

Length

2025-06-01T06:10:22.744515image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-06-01T06:10:22.887714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
user5 1033
10.3%
user1 1025
10.2%
admin 1023
10.2%
user3 1006
10.1%
system 1005
10.1%
user6 1000
10.0%
user4 994
9.9%
guest 990
9.9%
user2 967
9.7%
project 957
9.6%

Most occurring characters

ValueCountFrequency (%)
e 8977
17.0%
s 8020
15.2%
r 6982
13.2%
U 6025
11.4%
t 2952
 
5.6%
m 2028
 
3.8%
5 1033
 
2.0%
1 1025
 
1.9%
d 1023
 
1.9%
A 1023
 
1.9%
Other values (14) 13831
26.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 52919
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 8977
17.0%
s 8020
15.2%
r 6982
13.2%
U 6025
11.4%
t 2952
 
5.6%
m 2028
 
3.8%
5 1033
 
2.0%
1 1025
 
1.9%
d 1023
 
1.9%
A 1023
 
1.9%
Other values (14) 13831
26.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 52919
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 8977
17.0%
s 8020
15.2%
r 6982
13.2%
U 6025
11.4%
t 2952
 
5.6%
m 2028
 
3.8%
5 1033
 
2.0%
1 1025
 
1.9%
d 1023
 
1.9%
A 1023
 
1.9%
Other values (14) 13831
26.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 52919
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 8977
17.0%
s 8020
15.2%
r 6982
13.2%
U 6025
11.4%
t 2952
 
5.6%
m 2028
 
3.8%
5 1033
 
2.0%
1 1025
 
1.9%
d 1023
 
1.9%
A 1023
 
1.9%
Other values (14) 13831
26.1%

syscheck.arch
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size602.9 KiB
x86
2592 
AMD64
2529 
arm64
2458 
x86_64
2421 

Length

Max length6
Median length5
Mean length4.7237
Min length3

Characters and Unicode

Total characters47237
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAMD64
2nd rowx86
3rd rowx86
4th rowx86
5th rowx86

Common Values

ValueCountFrequency (%)
x86 2592
25.9%
AMD64 2529
25.3%
arm64 2458
24.6%
x86_64 2421
24.2%

Length

2025-06-01T06:10:23.093002image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-06-01T06:10:23.220289image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
x86 2592
25.9%
amd64 2529
25.3%
arm64 2458
24.6%
x86_64 2421
24.2%

Most occurring characters

ValueCountFrequency (%)
6 12421
26.3%
4 7408
15.7%
x 5013
10.6%
8 5013
10.6%
A 2529
 
5.4%
M 2529
 
5.4%
D 2529
 
5.4%
a 2458
 
5.2%
r 2458
 
5.2%
m 2458
 
5.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 47237
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
6 12421
26.3%
4 7408
15.7%
x 5013
10.6%
8 5013
10.6%
A 2529
 
5.4%
M 2529
 
5.4%
D 2529
 
5.4%
a 2458
 
5.2%
r 2458
 
5.2%
m 2458
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 47237
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
6 12421
26.3%
4 7408
15.7%
x 5013
10.6%
8 5013
10.6%
A 2529
 
5.4%
M 2529
 
5.4%
D 2529
 
5.4%
a 2458
 
5.2%
r 2458
 
5.2%
m 2458
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 47237
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
6 12421
26.3%
4 7408
15.7%
x 5013
10.6%
8 5013
10.6%
A 2529
 
5.4%
M 2529
 
5.4%
D 2529
 
5.4%
a 2458
 
5.2%
r 2458
 
5.2%
m 2458
 
5.2%

agent.name
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size663.9 KiB
PC-GAMER
1060 
SERVER-001
1024 
HOME-PC
1015 
DESKTOP-5JEIKFF
1015 
LAPTOP-1234
1006 
Other values (5)
4880 

Length

Max length15
Median length13
Mean length10.9671
Min length7

Characters and Unicode

Total characters109671
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWIN-LAPTOP
2nd rowDESKTOP-XYZ
3rd rowWORKSTATION-01
4th rowLAPTOP-1234
5th rowDESKTOP-XYZ

Common Values

ValueCountFrequency (%)
PC-GAMER 1060
10.6%
SERVER-001 1024
10.2%
HOME-PC 1015
10.2%
DESKTOP-5JEIKFF 1015
10.2%
LAPTOP-1234 1006
10.1%
DESKTOP-XYZ 1000
10.0%
DESKTOP-ALPHA 986
9.9%
SERVER-BETA 977
9.8%
WIN-LAPTOP 962
9.6%
WORKSTATION-01 955
9.6%

Length

2025-06-01T06:10:23.379624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-06-01T06:10:23.535389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
pc-gamer 1060
10.6%
server-001 1024
10.2%
home-pc 1015
10.2%
desktop-5jeikff 1015
10.2%
laptop-1234 1006
10.1%
desktop-xyz 1000
10.0%
desktop-alpha 986
9.9%
server-beta 977
9.8%
win-laptop 962
9.6%
workstation-01 955
9.6%

Most occurring characters

ValueCountFrequency (%)
E 11070
 
10.1%
- 10000
 
9.1%
P 9998
 
9.1%
O 7894
 
7.2%
T 7856
 
7.2%
A 6932
 
6.3%
R 6017
 
5.5%
S 5957
 
5.4%
K 4971
 
4.5%
0 3003
 
2.7%
Other values (21) 35973
32.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 109671
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 11070
 
10.1%
- 10000
 
9.1%
P 9998
 
9.1%
O 7894
 
7.2%
T 7856
 
7.2%
A 6932
 
6.3%
R 6017
 
5.5%
S 5957
 
5.4%
K 4971
 
4.5%
0 3003
 
2.7%
Other values (21) 35973
32.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 109671
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 11070
 
10.1%
- 10000
 
9.1%
P 9998
 
9.1%
O 7894
 
7.2%
T 7856
 
7.2%
A 6932
 
6.3%
R 6017
 
5.5%
S 5957
 
5.4%
K 4971
 
4.5%
0 3003
 
2.7%
Other values (21) 35973
32.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 109671
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 11070
 
10.1%
- 10000
 
9.1%
P 9998
 
9.1%
O 7894
 
7.2%
T 7856
 
7.2%
A 6932
 
6.3%
R 6017
 
5.5%
S 5957
 
5.4%
K 4971
 
4.5%
0 3003
 
2.7%
Other values (21) 35973
32.8%
Distinct5697
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Memory size820.4 KiB
2025-06-01T06:10:23.954188image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length27
Median length27
Mean length27
Min length27

Characters and Unicode

Total characters270000
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2859 ?
Unique (%)28.6%

Sample

1st rowMay 15, 2025 @ 06:44:44.990
2nd rowMay 19, 2025 @ 18:25:07.043
3rd rowMay 02, 2025 @ 19:13:50.756
4th rowMay 28, 2025 @ 07:58:43.795
5th rowMay 04, 2025 @ 21:38:31.412
ValueCountFrequency (%)
2025 10000
20.0%
10000
20.0%
may 9926
19.9%
14 391
 
0.8%
25 380
 
0.8%
15 371
 
0.7%
16 358
 
0.7%
31 358
 
0.7%
07 351
 
0.7%
03 350
 
0.7%
Other values (5722) 17515
35.0%
2025-06-01T06:10:24.458144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40000
14.8%
2 35551
13.2%
0 27384
10.1%
5 20203
 
7.5%
: 20000
 
7.4%
1 18193
 
6.7%
3 11247
 
4.2%
4 10210
 
3.8%
@ 10000
 
3.7%
. 10000
 
3.7%
Other values (11) 67212
24.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 270000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
40000
14.8%
2 35551
13.2%
0 27384
10.1%
5 20203
 
7.5%
: 20000
 
7.4%
1 18193
 
6.7%
3 11247
 
4.2%
4 10210
 
3.8%
@ 10000
 
3.7%
. 10000
 
3.7%
Other values (11) 67212
24.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 270000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
40000
14.8%
2 35551
13.2%
0 27384
10.1%
5 20203
 
7.5%
: 20000
 
7.4%
1 18193
 
6.7%
3 11247
 
4.2%
4 10210
 
3.8%
@ 10000
 
3.7%
. 10000
 
3.7%
Other values (11) 67212
24.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 270000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
40000
14.8%
2 35551
13.2%
0 27384
10.1%
5 20203
 
7.5%
: 20000
 
7.4%
1 18193
 
6.7%
3 11247
 
4.2%
4 10210
 
3.8%
@ 10000
 
3.7%
. 10000
 
3.7%
Other values (11) 67212
24.9%

Interactions

2025-06-01T06:10:12.406264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-01T06:10:11.421000image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-01T06:10:11.918191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-01T06:10:12.550903image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-01T06:10:11.588227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-01T06:10:12.094052image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-01T06:10:12.699435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-01T06:10:11.747334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-01T06:10:12.259141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-06-01T06:10:24.578543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
agent.namesyscheck.archsyscheck.changed_attributessyscheck.eventsyscheck.size_aftersyscheck.size_beforesyscheck.uid_aftersyscheck.uname_after
agent.name1.0000.0000.0040.0000.0180.0170.0080.010
syscheck.arch0.0001.0000.0030.0090.0170.0000.0120.000
syscheck.changed_attributes0.0040.0031.0000.0000.0000.0120.0180.016
syscheck.event0.0000.0090.0001.0000.0000.0000.0000.000
syscheck.size_after0.0180.0170.0000.0001.0000.8980.0170.000
syscheck.size_before0.0170.0000.0120.0000.8981.0000.0140.005
syscheck.uid_after0.0080.0120.0180.0000.0170.0141.0000.016
syscheck.uname_after0.0100.0000.0160.0000.0000.0050.0161.000

Missing values

2025-06-01T06:10:13.669853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-06-01T06:10:13.926482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

syscheck.eventsyscheck.pathsyscheck.attrs_aftersyscheck.changed_attributessyscheck.size_beforesyscheck.size_aftersyscheck.mtime_beforesyscheck.mtime_aftersyscheck.md5_beforesyscheck.md5_aftersyscheck.uid_aftersyscheck.uname_aftersyscheck.archagent.name@timestamp
0modifiedE:\Data\resource.pdfread,write,hidden,systemowner,mode16086662099709May 20, 2025 @ 21:37:28May 20, 2025 @ 22:01:235561e1c0a579fab5c129c76ef2995e4062566fb197ee2c934aced8f5491db1aba068c40f0c8cdabad580b70297ad0e3d070d49403ebc0b48218b6ca6c750fe196854User4AMD64WIN-LAPTOPMay 15, 2025 @ 06:44:44.990
1deletedD:\Work\three.batexec,archive,writemode,size130407489904May 16, 2025 @ 20:41:05May 16, 2025 @ 20:43:153c7631e0f7496bea8ee63d79d28969a4d81982030bd0914a919040c0b0f32fc196e1a43126806263aa4f49243f404651731446a290778adcac5ce9e3ed0c7dda8765User2x86DESKTOP-XYZMay 19, 2025 @ 18:25:07.043
2deletedC:\Users\Project\Documents\success.jpgarchive,readgroup218982487333May 11, 2025 @ 19:48:23May 11, 2025 @ 20:24:27445d870daa4fd41447c47a82550b17441706755f7699bfd8e70dba2f8007002e9cdd8b840a7d5609047e6a45f2f2e96b1cb4a6750ec5c82c9ba6b5c000a181131104Systemx86WORKSTATION-01May 02, 2025 @ 19:13:50.756
3addedD:\Work\career.dllhidden,archivemtime14725691050226May 24, 2025 @ 06:14:30May 24, 2025 @ 06:40:59035cfdbd8ccc19822ffe29ef0d53d8100e262ea08bddf45e524c2d5cc7184f60236e336691c3df827e1cef726a7a44dee65a3e86abb6855c537ef4fa186a12551661User4x86LAPTOP-1234May 28, 2025 @ 07:58:43.795
4modifiedC:\Windows\Temp\field.batsystem,read,hiddenmode916006725192May 26, 2025 @ 13:20:09May 26, 2025 @ 14:14:227c42e63ce655761f78d841e46c541cbb10cd79a8b2c8e4fa05537427ad316eee58c48678ab5e2bfec68d3e4ef15beda80b49877796539677af9d166f99483f645993User1x86DESKTOP-XYZMay 04, 2025 @ 21:38:31.412
5modifiedC:\Users\User2\Desktop\tough.ziparchive,exec,hiddensize,group297462715887May 10, 2025 @ 10:14:17May 10, 2025 @ 10:17:106575939643b2e963735f4a92ce793cdee1c401b9b3a3109a441b25f396543041e6a47d6d265ec42036bec9b0b6585bc15261ba20a340759397c686a250ee63ee4439Projectx86LAPTOP-1234May 30, 2025 @ 10:41:19.066
6deletedC:\Windows\Temp\war.dllarchive,hidden,system,readgroup1486500988872May 13, 2025 @ 05:44:48May 13, 2025 @ 05:45:47a0a9141f79f4cae63fb7ccd4016a88967c6eb11e715421f183db9e9b1912d94d4f60e5e78ed4992e586fa8d4cfb24a6f1449Adminx86_64DESKTOP-ALPHAMay 14, 2025 @ 04:03:06.951
7deletedC:\Users\Project\Documents\significant.dllsystem,hidden,archive,readsize,mode13282151062382May 22, 2025 @ 16:50:37May 22, 2025 @ 16:56:3536dbf41e72e21fc2d674102ed1310a588697554b006ab539982469bebeb1d912cfef33b93ba3ec1f788802a30efbeb873063User4AMD64LAPTOP-1234May 31, 2025 @ 21:57:04.124
8addedC:\Windows\Temp\guess.pdfsystem,readmtime740819940744May 18, 2025 @ 18:05:11May 18, 2025 @ 19:00:1235dfc63318e3e621ab9dbacf5378498cb95c88a498d329c89b2f4f1aa76124906107b4660b3c65ff1303581c0b38e59c3a36bda0892d6304df7b5b4805778ea45573Adminarm64DESKTOP-ALPHAJun 01, 2025 @ 05:51:26.336
9modifiedE:\Data\white.docxexec,archive,hidden,writeowner,mtime2525261May 07, 2025 @ 22:04:07May 07, 2025 @ 22:41:5736aef7ae846389f9fb9d7ef02a783c8a3ce6439fbafbc8b0ef6d00c8041faffb62c99ab36c7970d21b2a3339b41061fdab6a08c8299c22c7b810abe53c1ad27b8643User1x86PC-GAMERMay 04, 2025 @ 09:41:23.240
syscheck.eventsyscheck.pathsyscheck.attrs_aftersyscheck.changed_attributessyscheck.size_beforesyscheck.size_aftersyscheck.mtime_beforesyscheck.mtime_aftersyscheck.md5_beforesyscheck.md5_aftersyscheck.uid_aftersyscheck.uname_aftersyscheck.archagent.name@timestamp
9990modifiedC:\Users\Project\Documents\scene.txtexec,archive,hiddenmtime,group629826392419May 03, 2025 @ 11:14:40May 03, 2025 @ 11:40:53b1000cfdb24c5b900706c006bcce0a34b98c879b45fbc00424603e59af1f41c87e51e6841c766ecfcc17839fc7916b519edf3215b9e1fad3803f33d46de22d474155AdminAMD64DESKTOP-ALPHAMay 13, 2025 @ 03:19:29.801
9991deletedC:\Windows\System32\help.txtsystem,read,archive,hiddenmode,size19579425429May 03, 2025 @ 01:31:21May 03, 2025 @ 02:15:080b4e36e6579cfc2f95f8991eff48c35adc6b4ae539edbeb326498fcbec795b5d5d9af838090bb7789127d8077babd7948bdd39dd6cf1472975df1393b74a28d21698User2x86DESKTOP-XYZMay 22, 2025 @ 00:56:31.906
9992addedC:\Users\User1\Downloads\available.exeexec,write,readowner,mtime12053201335478May 18, 2025 @ 23:00:29May 18, 2025 @ 23:27:0093a2f1d1ef05c338d14b0ecf16f323dbfe8d32f5ee369f768cbc6a19bdd6c31862aaa7f1e6f3034f72689a4c301155354563AdminAMD64SERVER-BETAMay 11, 2025 @ 19:16:54.912
9993modifiedD:\Work\control.dllsystem,hidden,exec,archivegroup,size19148881976907May 12, 2025 @ 15:28:57May 12, 2025 @ 15:30:189ad3cfc2ab9698ee7a21682dc1119451ae67606512d3d92fd9a5eae594cc065b46fc34aa07a0e1cce28ab6d08f983b5cf5643dc320046d64967dee158b7e7c665604Projectx86_64WIN-LAPTOPMay 29, 2025 @ 07:39:08.584
9994deletedC:\Users\Guest\Documents\small.txtread,systemsize,group486724301735May 07, 2025 @ 20:11:46May 07, 2025 @ 20:15:3898873efb21e9d8b9450880e561cc67890b6d3791b51f64c8f3203e75a249b03689d5e60d574ff26ed99bc30e62fb18257841Projectarm64LAPTOP-1234May 27, 2025 @ 21:51:15.498
9995modifiedE:\Data\watch.dllexec,system,write,hiddengroup,owner31337894002May 03, 2025 @ 16:38:04May 03, 2025 @ 17:20:31fdcb657c6ca01aced07a7e488f14f78087cecda432829303ba4ed55aad1b247ea065ec2185b6f9d542a9c2baafe224c0b649c7843ef97ae5881f4a5ccc80cc154147User2AMD64SERVER-BETAMay 21, 2025 @ 10:33:15.221
9996addedC:\Windows\Temp\people.exeread,exec,system,hiddengroup16371661564962May 21, 2025 @ 20:41:11May 21, 2025 @ 20:44:5708195a877795169d106ba45b3a818b229736dce896a69c65ec76aebc347a216d8fd107232013d0ce39d2832ac16e60ff6e4f3e669f3fbbc00df90282b47009494136User2x86WIN-LAPTOPMay 31, 2025 @ 12:17:16.159
9997deletedC:\Users\User2\Desktop\hospital.dllsystem,read,hiddengroup15785591737606May 06, 2025 @ 13:52:14May 06, 2025 @ 14:18:314dda1447c5cfad0023c6fbf0d8f65e7c79cb553c0e27c7882c0310c8841ca67d8e4f6f67035aabaf77ad259add9e33e69c8ae0896c36bc4bf21f097bc60cce417374User5x86_64SERVER-001May 15, 2025 @ 02:13:23.385
9998addedC:\Users\Project\Documents\community.docxsystem,read,hidden,archivesize,mode775285487456May 30, 2025 @ 11:47:20May 30, 2025 @ 12:42:259646a70c9d46ef5ca33cb12c608a18dbd5b182f811ba39c14f910490ad6fd35ac3898bd8f2f315606b5ab989cdc4af351e7072d04687ddc377a007146b1fe6fa2504User2x86LAPTOP-1234May 09, 2025 @ 00:14:35.391
9999addedE:\Data\western.dllexec,systemmtime,group839680380902May 07, 2025 @ 19:18:10May 07, 2025 @ 20:00:51f282ec7c291eb4fde6cfddb8ad5d0ef7930bd4cbd3a710ef50b265ca17ded292fd0a0cb373767df8cd734af56f7cf90e3948Guestx86SERVER-BETAMay 17, 2025 @ 01:07:55.216